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Finally, the article puts forward relevant suggestions for sustainable development based on the resource and environmental foundation and characteristics of Qilihai Wetland.The successful launch of the Sentinel-2 constellation satellite, along with advanced cloud detection algorithms, has enabled the generation of continuous time series at high spatial and temporal resolutions, which is in turn expected to enable the classification of salt marsh vegetation over larger spatiotemporal scales. This study presents a critical comparison of vegetation index (VI) and curve fitting methods-two key factors for time series construction that potentially influence vegetation classification performance. To accomplish this objective, the stability of five different VI time series, namely Normalized Difference Vegetation Index (NDVI), Soil-Adjusted Vegetation Index (SAVI), Enhanced Vegetation Index (EVI), Green Normalized Difference Vegetation Index (GNDVI), and Water-Adjusted Vegetation Index (WAVI), was compared empirically; the suitability between three curve fitting methods, namely Asymmetric Gaussian (AG), Double Logistic (DL), and Two-term Fourier (TF), and VI time series was measured usl climate, whilst the SAVI/NDVI-based TF model appears to be better suited to mid- to low latitude regions dominated by a monsoonal climate.Protein homeostasis (proteostasis) disturbances and inflammation are evident in normal aging and some age-related neurodegenerative diseases. While the proteostasis network maintains the integrity of intracellular and extracellular functional proteins, inflammation is a biological response to harmful stimuli. Cellular stress conditions can cause protein damage, thus exacerbating protein misfolding and leading to an eventual overload of the degradation system. The regulation of proteostasis network is particularly important in postmitotic neurons due to their limited regenerative capacity. Therefore, maintaining balanced protein synthesis, handling unfolding, refolding, and degrading misfolded proteins are essential to preserve all cellular functions in the central nervous sysytem. Failing proteostasis may trigger inflammatory responses in glial cells, and the consequent release of inflammatory mediators may lead to disturbances in proteostasis. Here, we review the mechanisms of proteostasis and inflammatory response, emphasizing their role in the pathological hallmarks of neurodegenerative diseases such as Alzheimer’s disease, Parkinson’s disease, and amyotrophic lateral sclerosis. Furthermore, we discuss the interplay between proteostatic stress and excessive immune response that activates inflammation and leads to dysfunctional proteostasis.Improving farm animal welfare requires modifications to the behavior of many stakeholders. Investments in more animal-friendly barns to improve animal welfare have already been made by some farmers. However, more farmers must be persuaded to modernize their barns. The marketing of animal-friendly products is the responsibility of retailers, and consumers have to purchase these products. Currently, little is known about what (and how) underlying psychological factors influence a farmer’s intention to construct pig housing to improve farm animal welfare. Pig farmers in Germany were questioned via an online questionnaire in May 2020 (n = 424). Based on the Theory of Planned Behavior (TPB), partial least squares path modeling was used. The constructs attitude, subjective norm, direct and indirect experience associated with the construction of pig housing substantially influenced the farmers’ behaviors. As expected, the impact of perceived behavioral control on intention was negative but was also very low and only slightly significant. Contrary to expectations, the perceived behavioral control had no significant influence on farmers’ behaviors. Pig farmers who have already rebuilt their pigs’ housing should be motivated to share their experiences to influence their colleagues’ intentions to construct. Our results will encourage policy makers to consider the important role of the different psychological and intrinsic factors influencing pig farmers. Thus, the sustainability of pig farming can be improved by giving politicians a better understanding of farmers´ behaviors.Visual-based object detection and understanding is an important problem in computer vision and signal processing. Due to their advantages of high mobility and easy deployment, unmanned aerial vehicles (UAV) have become a flexible monitoring platform in recent years. However, visible-light-based methods are often greatly influenced by the environment. As a result, a single type of feature derived from aerial monitoring videos is often insufficient to characterize variations among different abnormal crowd behaviors. To address this, we propose combining two types of features to better represent behavior, namely, multitask cascading CNN (MC-CNN) and multiscale infrared optical flow (MIR-OF), capturing both crowd density and average speed and the appearances of the crowd behaviors, respectively. First, an infrared (IR) camera and Nvidia Jetson TX1 were chosen as an infrared vision system. Since there are no published infrared-based aerial abnormal-behavior datasets, we provide a new infrared aerial dataset named the IR-flying dataset, which includes sample pictures and videos in different scenes of public areas. Second, MC-CNN was used to estimate the crowd density. Third, MIR-OF was designed to characterize the average speed of crowd. Finally, considering two typical abnormal crowd behaviors of crowd aggregating and crowd escaping, the experimental results show that the monitoring UAV system can detect abnormal crowd behaviors in public areas effectively.The transepidermal water loss (TEWL) and the skin wettedness factor (SWF) are considered parts of a key perspective related to skincare. The former is used to determine the loss of water content from the stratum corneum (SC), while the latter is used to determine the human skin comfort level. Herein, we developed two novel approaches (1) determination of the TEWL and the SWF based on a battery-free humidity sensor, and (2) the design of a battery-free smart skincare sensor device tag that can harvest energy from a near field communication (NFC)-enabled smartphone, making it a battery-free design approach. The designed skincare device tag has a diameter of 2.6 cm and could harvest energy (~3 V) from the NFC-enabled smartphone. click here A series of experimental tests involving the participation of eight and six subjects were conducted in vivo for the indoor and outdoor environments, respectively. During the experimental analysis, the skin moisture content level was measured at different times of the day using an android smartphone.